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AFE Analyst of the Year

Rewarding Excellence in Accelerated Feature Extraction


Read first hand accounts and view photographs of some of the additional projects and events in which Feature Analyst® and LIDAR Analyst® have improved GIS efforts across the globe. Titles link to the full story.

Using Feature Analyst to Automate Counts of Photographed Indiana Bats

The Remote Sensing Applications Center conducted an exploratory investigation of the possibility of obtaining accurate counts of the photographed Indiana bat quickly and accurately using semi-automated digital image processing techniques. Feature Analyst was used to digitize the bats' muzzles as they hibernated. Click on the link above to review the results.

Mapping Illicit Crop Production

Mike Diller has been using Feature Analyst to map illicit crop production. The award was presented at the 2008 Overwatch Geospatial Users Conference.

Feature Analyst: Applications Abound

Jason San Souci, Director, Geospatial Applications, of the Native Communities Development Corporation (NCDC). San Souciís submission highlighted a variety of NCDC projects that employed Feature Analyst to develop an advanced, multi-iteration accelerated feature extraction (AFE) methodology used to classify image datasets. For a demonstration of a typical Feature Analyst workflow for a civil government project, view his video here.

Feature Analyst Technology Enables NCDC to Assess Wildfire Risk

NCDC identified high density timber areas and individual tree crowns along with buildings and other flammable structures using Feature Analyst for its rapid, accurate extraction capability. In visual illustrations, NCDC shows the critical response advantages of using Feature Analyst in the event of a wildfire.

NOAA-funded Research Develops Mapping Prototype to Benefit Oyster Resources

Using Feature Analyst, NOAA (National Oceanic & Atmospheric Administration) has created the precedent for mapping oyster reefs. With the model in place, resource managers can obtain more timely information on the changing condition of oyster resources and better determine the steps required for restoration.

Submit your own success story using AFE technology for a chance to win the AFE Analyst of the Year award. Review the submission guidelines below and take a look at our nominees.

Formatting requirements on paper submissions are as follows: (1) send a detailed, typewritten document, preferably .doc format or .rtf; (2) include captions or descriptions for all images; and (3) images may be embedded in the document or attached separately, preferably in .tif, .png, .jpg, .bmp, or .gif format.

Submit papers less than 10MB via email to sales@vls-inc.com. For papers larger than 10MB and for more information about this award, contact VLS and a representative will be happy to assist you.

*Note: Any entries to the AFE Analyst of the Year contest may be used in informational or promotional materials for the contest or for Overwatch as a company. By entering into the AFE Analyst of the Year contest, you grant permission to Overwatch to reproduce your publication in electronic or print format for Overwatch marketing purposes, including, but not limited to Web site content, company newsletters, brochures, and videos.


"Timing comparisons indicate that Feature Analyst reduces extraction time by a factor of 5 to 10 over small areas. By using Feature Analyst to develop accelerated feature extraction (AFE) models over a small training set and then applying the models to larger areas, extraction times could be reduced by several orders of magnitude."

Mike O'Brien, National Geospatial-Intelligence Agency (NGA) STAR Program Manager, ASPRS International Conference 2003

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